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I am an interdisciplinary researcher with over 15 years of experience in biomedical informatics, AI, and health data science. My work spans machine learning, natural language processing, and multi-omics integration for clinical and translational research. I have led international teams, published extensively in peer-reviewed journals, and served as an associate editor in top scientific publications. I specialize in developing scalable, data-driven solutions for complex biomedical challenges.
Senior full stack commercial software developer with 9 years of experience put of which the past 7 years are Flutter/Dart based while utilizing various tech stacks such as: RESTful APIs, Node.js, Google Cloud Platform, Firebase, Payment gateways (PayPal and Stripe), AI, ML, LLMs and many more. I have developed over 20+ applications of various scales and dynamics. I have a Master's Degree in Advanced Computer Science and Bachelor's Degree in Computer Science.
I'm Alex, with 7 years of cloud operations experience. I specialize in optimizing cloud resources on platforms like Alibaba Cloud, Tencent Cloud, AWS, and Google Cloud. I've led projects that reduced cloud costs by over 20%, saving millions annually, and improved service availability. I offer cloud infrastructure planning, operations process establishment, cost management, and resource optimization services. My proactive approach and dedication ensure high-quality, timely project delivery.
Experienced AI/ML and Data Engineer with a strong foundation in Python development, access control data analysis, and cloud platforms like AWS and Azure. Skilled in building APIs, dashboards, and data workflows for security, reporting, and compliance. Proven expertise in integrating AI models, LLMs, and Power BI for actionable insights. Track record of delivering high-impact solutions across industries including credit, insurance, and healthcare.
I am a data-driven builder with over five years of work in data, AI, and cloud tech. I turn raw input into models, tools, and clear insight for teams and clients. I have strong skill in Python, SQL, and Power BI. I have worked with cloud apps, APIs, and large AI tools to solve real goals in fast setups. I ask the right questions, move with care, and shape each task to fit the need. My focus is always on value, clarity, and trust in the result.
My professional background and experience has centered around leading code implementations within project executions, interfacing with clients in order to understand their needs and requirements, as well as advancing data pipeline architectures, which are crucial for migrating data workloads to, as well as building AI applications within the Google Cloud Platform. My contributions (from design to delivery) have enabled efficient and scalable data solutions, reducing infrastructure costs significantly. Within this dynamic environment, my proficiency in Data Engineering, AI, as well as knowledge of Machine learning Operations has been pivotal to successfully transitioning complex analytics workloads to cloud-based platforms.
I am a results-driven Data Engineer with over 3 years of experience in building scalable ETL/ELT pipelines, optimizing data workflows, and ensuring data accuracy. Proficient in Python, SQL, and big data tools like Spark and Hive, I specialize in designing and implementing cloud-based data systems using AWS and data orchestration using Apache Airflow/Autosys. My expertise includes data modeling, query optimization, and stream processing. I thrive in collaborative, agile environments and am committed to delivering high-quality, reliable data solutions to support data-driven decision-making.
At Techamana, we maintain the highest standards in developer selection. Our Big Data experts undergo a comprehensive 4-step vetting process that evaluates technical skills, problem-solving abilities, communication skills, and team and culture fit. Only the top 5% of applicants pass our rigorous screening, ensuring you work with exceptional talent who can deliver outstanding results for your projects.
Rigorous coding challenges and problem-solving tests to evaluate Big Data proficiency and best practices.
Thorough examination of past projects and contributions to open-source Big Data repositories to assess real- world experience.
Video responses for open-ended questions to assess problem-solving ability, communication skills, and team and culture fitment.
When hiring a Big Data engineer, seek Hadoop and Spark proficiency for distributed processing.
Candidates should optimize ETL pipelines, manage data lakes (S3/HDFS), implement real-time streaming (Kafka/Flink), and tune clusters for reliable analytics.
Industry insights and best practices
Big data involves collecting, storing, processing, and analyzing large and complex datasets. Modern big data technologies utilize distributed systems and advanced analytics.
Data warehousing involves designing databases for storing and analyzing large amounts of data for business intelligence.
Big data is often used to train machine learning models, providing large datasets for model training and validation.
Real-time analytics on big data allows businesses to make timely decisions based on current data trends.
Predictive modeling using big data allows businesses to forecast future trends and make proactive decisions.
Majority of our clients choose to continue working with our talent after their initial project
Our screening and matching process ensures exceptional talent are matched to your precise needs.
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